metadata
language:
- hy
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Large-v2 Armenian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 hy-AM
type: mozilla-foundation/common_voice_11_0
config: hy-AM
split: test
args: hy-AM
metrics:
- name: Wer
type: wer
value: 40.23026315789473
Whisper Large-v2 Armenian
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 hy-AM dataset. It achieves the following results on the evaluation set:
- Loss: 0.4429
- Wer: 40.2303
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0113 | 8.02 | 200 | 0.3501 | 43.7171 |
| 0.0003 | 17.01 | 400 | 0.3989 | 40.7895 |
| 0.0001 | 26.0 | 600 | 0.4282 | 40.4605 |
| 0.0001 | 34.02 | 800 | 0.4392 | 40.2632 |
| 0.0001 | 43.01 | 1000 | 0.4429 | 40.2303 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2